Implementing Fuzzy Reasoning by IAF Neurons

Implementing of intersection operation and union operation in fuzzy reasoning is explored by three Integrate-And-Fire (IAF) neurons, with two neurons as inputs and the other one as output. We prove that if parameter values of the neurons are set appropriately for intersection operation, firing rate of the output neuron is equal to or is lower than the lower one of two input neurons. We also prove that if parameter values of the neurons are set appropriately for union operation, the firing rate of the output neuron is equal to or is higher than the higher one of the two input neurons. The characteristic of intersection operation and union operation implemented by IAF neurons is discussed.

Authors and Affiliations

1. College of Information Science and Technology, Donghua University, 200051, Shanghai, China

   Zhijie Wang

2. Glorious Sun School of Business and Management, Donghua University, 200051, Shanghai, China

   Hong Fan

Editors and Affiliations

1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

   Lipo Wang

2. School of Software, Sun Yat-Sen University, 510275, Guangzhou, China

   Ke Chen

3. School of Computer Engineering, Nanyang Technological University, BLK N4, 2b-39, Nanyang Avenue, 639798, Singapore

   Yew Soon Ong

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